The application relates to radio system technologies and, in particular, to an apparatus and a method for cross-domain analysis of radio systems. Particularly, the application relates to state analysis and fault analysis in industrial radio systems, commercial radio systems and also private radio systems.
Nowadays, radio communication systems are employed in many fields, like in industrial automation for data connection of mobile or movable subsystems to higher systems, in different fields of companies, and in large public areas, like stations, airports, trade fair halls and hospitals. Many of the radio systems employed use license-free frequency bands, like ISM (Industrial, Scientific and Medical) frequency bands or UNII (Unlicensed National Information Infrastructure) frequency bands.
However, problems arise when using license-free frequency bands. On the one hand, the frequency bands are employed by a plurality of radio protocols (like Bluetooth, WiFi, etc.) and also differing technical facilities (like by a microwave). Since the access of spatially neighboring radio networks to the radio medium is not coordinated centrally, mutual interference or faults between the radio networks, referred to as coexistence problems, may arise. Temporal, spatial and spectral superpositioning of different radio signals and, partly, the delay of emitting a radio signal due to the radio channel being occupied by another radio signal are among these problems.
In addition, one problem is that the application using radio networking does not receive, or only to a very limited extent, information on the state of the radio transmission system. The radio components employed do not, or not sufficiently, comprise ways of monitoring the state of radio networking since the hardware resources available thereof are very limited. In the case of transmission faults, the radio components are not able to identify the cause of the transmission faults by themselves.
Among other things, spectral analyzers are used for solving the above problems in known technology: operating the measuring apparatuses and interpreting the measuring results are done manually and need a profound knowledge of radio systems. However, this only allows roughly recognizing which radio protocols are used by the radio-frequency (or high-frequency) band measured and which receive power the radio protocols are measured with. Using this solution approach, however, no further information (like occupancy of the frequency band, duration of the radio signals, addresses of the radio nodes) can be detected. The RSA7100A Spectrum Analyzer by Tektronix is an example of such a spectral analyzer (see [3]: https://www.tek.com/datasheet/rsa7100a:RSA7100A).
A further known approach is using protocol analyzers. Known protocol analyzers are designed for one radio protocol (like WiFi) and analyze the contents of radio packets recorded. Due to the limitation to a specific radio protocol and the evaluation of radio packet contents, the protocol analyzers are not able to identify mutual interferences (coexistence problems) between neighboring radio systems using different radio protocols. Examples of protocol analyzers are, for example, the WiFi analyzers: NetScout—AirMagnet (see [4]: http://enterprise-de.netscout.com/enterprise-network/wireless-network/AirMagnet-WiFi-Analyzer).
In addition, combinations of spectrum analyzers and WiFi protocol analyzers are known from known technology. An example of this is NetScout—AirMagnet Spectrum XT (see [5]: http://enterprise-de.netscout.com/content/datasheet-airmagnet-spectrum-xt). This solution/approach automatically analyzes the radio spectrum and recognizes radio protocols (like WiFi, Bluetooth, etc.) using patterns. The information are made visible in the protocol analysis. A detailed spectral analysis of each radio signal and an evaluation based thereon, for example as to channel occupancy or distribution of the receive power per radio protocol, is not performed.
U.S. Pat. No. 7,184,777 B2 (see [6]) refers to the management of usage of the radio-frequency spectrum by means of identification, classification and localization of emissions in a radio-frequency band. A distributed system of “radio sensor apparatuses” is illustrated, which each include an RF receiver with a spectrogram analysis connected thereto and another RF receiver having a demodulator for a certain radio protocol. A spectrogram analysis provides information for using the radio-frequency band monitored (so-called activity information).
EP 3 170 333 A1 (see [7]) discloses a system of distributed spectrogram analysis nodes. In some examples, the wireless spectrogram analysis system comprises radio spectrum analysis apparatuses which are distributed to different locations across a geographical region. The radio spectrum analysis apparatuses are configured so as to simultaneously monitor the radio spectrum utilization at each individual location.
US 2003 0198200 A1 (see [8]) relates to performing a spectrogram analysis and using the information for managing several radio nodes. Information for using the radio-frequency band monitored are calculated and these so-called activity information are used for controlling and managing radio nodes.
US 2009 0052500 A1 (see [9]) shows an apparatus comprising a spectrum analyzer and a decision circuit. The spectrum analyzer is configured to establish wireless signal signature data from a broad range of frequency bands.
US 2007 0264939 A1 (see [10]) shows a method for identifying apparatuses, wherein pulse metrics data represent characteristics which are associated to impulses of radio-frequency energies received. Based on their pulse metrics data, the pulses are subdivided into groups so that one group comprises pulses having similarities for at least one pulse metrics data unit.
In [1], for the first time, a hardware suggestion for a radio analysis apparatus has been presented which, apart from a module for spectral analysis, comprises separate receive modules for three different radio protocols, WiFi, Bluetooth, IEEE 802.15.4. The suggestion of spectral analysis and protocol analysis as illustrated in [1] is also presented in [2].